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Record W1972862995 · doi:10.1675/063.037.0106

Assessing the Breeding Success of the Western Grebe (<i>Aechmophorus occidentalis</i>) After 40 Years of Environmental Changes at Delta Marsh, Manitoba

2014· article· en· W1972862995 on OpenAlexaffabout
Nicholas La Porte, Nicola Koper, Lionel Leston

Bibliographic record

VenueWaterbirds · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNest (protein structural motif)MarshDeltaTyphaEcologyHabitatBiologyVegetation (pathology)Water levelWetlandGeography

Abstract

fetched live from OpenAlex

Since the 1970s, artificially stabilized water levels, increased presence of common carp (Cyprinus carpio) and invasion by a cattail hybrid (Typha × glauca) have changed the nesting environment for Western Grebes (Aechmophorus occidentalis) at Delta Marsh, Manitoba. To evaluate the impact of these changes, nest survival rates, causes of nest mortality, wind conditions, locations of nests and vegetation structure at nests in 2009–2010, and chick-adult ratios were compared to similar data for Western Grebes at Delta Marsh from 1973–1974. Apparent nest survival rates were lower in 2009–2010 than 1973–1974, and between low-water years (1973, 2010) and high-water years (1974, 2009). Lower apparent nest survival rates in 2009–2010 (49% in 2009 and 43% in 2010, compared to 46% in 1973 and 84% in 1974), and chick-adult ratios (0.55 in 1973 and 0.88 in 1974, compared to 0.55 in 2009 and 0.39 in 2010) were attributed to increases in destruction of nests primarily by wave action and secondarily by common carp, which were not observed destroying Western Grebe nests in 1973–1974. The replacement of native bulrushes by cattails in Western Grebe nesting habitat may have caused the observed increase in proximity to openwater edge, and this proximity may have increased destruction of nests by waves. Restoring stands of emergent bulrush by varying marsh water levels and reducing carp in the marsh might improve nest survival of Western Grebes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.215
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2014
Admission routes2
Has abstractyes

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